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案例頻道作者：北京和利時智能技術有限公司，寧波和利時智能科技有限公司 范瑩，李天輝，劉宗福，姜百寧
摘要：為解決機器人故障預測問題，提出一種使用機器人軸溫預測的方法，實現機器人異常發熱的提前預警，避免故障的發生。本文使用生產中機器人的歷史數據作為數據源，分析對機器人軸溫產生影響的測點，結合機器人機理，對數據進行衍生轉換等操作，生成可以用于機器人軸溫預測的特征數據。鑒于沒有免費午餐（NFL，No Free Lunch）定理，對所有數據可用回歸算法進行自動化選擇，然后使用hyperopt進行優化調參，最終生成可用的機器人軸溫預測模型。本文中所述數據獲取、分析建模、上線部署及在線預測全部過程在HolliCube工業互聯網平臺上進行。
關鍵詞：溫度預測；故障診斷；機器人；工業互聯網平臺；運行周期
Abstract: Aiming at fault diagnosis for robots, a method which predicts robot's axes temperature is proposed to realize abnormal robot heating in advance and avoid the occurrence of faults. In this paper, the historical data of the robot in production are used as data source to analyze the measuring points which affect the axle temperature of the robot. Combined with the mechanism of the robot, the data are derived and converted to generate the characteristic data which can be used to predict the axle temperature of the robot. Then select regression algorithms automatically caused by the NFL theory, and then optimize the hyper-parameters by hyperopt and finally we got the model. The whole process of data acquisition, analysis and modeling, online deployment and online prediction described in this paper are carried out on HolliCube industrial Internet platform.
Key words: Temperature prediction; Fault diagnosis; Robot;Industrial internet platform; Running cycle
在線預覽：基于數據驅動的機器人軸溫預測建模與應用
摘自《自動化博覽》2019年10月刊
北京市公安局海淀分局備案號：11010802023656號